Factored Models for Morphology

We developed factored models for statistical machine translation
that represent each word as a vector of factors such as the surface form
of the word, its stem, its part of speech, and other morphological 
information. We report on experimental results of using such a representation
in phrase-based translation models and also present more recent work
on factored representation in grammar-based translation models.